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TA Training: Grading & Delivering Feedback on Quantitative Assignments

Evidence-based training for grading and providing feedback on quantitative work, including problem sets, code, and written responses.

 

Description

How can you grade efficiently, effectively, and fairly? How can you simultaneously give your students feedback that will maximize their learning? These online modules will focus on evidence-based strategies for grading and providing feedback on quantitative work, such as problem sets, code, and written responses. In these modules, participants will explore the relationship between grading and feedback, strategies for grading efficiently and fairly, the characteristics of effective feedback, and research on the impacts of different types of feedback on student learning. Through practice exercises, participants will practice analyzing and improving examples of feedback on student work. Participants will also practice grading and providing feedback using rubrics.

  • Audience: Graders, Instructors of record, TAs who facilitate recitation/lab/discussion/studio sections
  • Prerequisites: No prior knowledge is expected, but TAs of all experience levels can benefit from this training
  • Duration: approx. 90-120 minutes, including the pre- and post-assessments.

Please email eberly-assist@andrew.cmu.edu with questions or for help with setting up your TA Training course

What's included

  • Instructor Resources Module – for instructors only
  • Module 1: Grading and Feedback    
  • Module 2: Characteristics of effective feedback    
  • Module 3: Rubrics & efficiency strategies
  • Pre and Post Assessments
    • Our two assessments are isomorphic (they have the same structure but different examples) and are aligned with our 5 learning objectives. They each consist of 13 questions, including multiple choice, short answer, and authentic task questions.

Learning objectives

  • Identify characteristics of effective feedback.
  • Use a rubric to grade student work and provide feedback to improve student learning.
  • Describe strategies for grading effectively, efficiently, and fairly.
  • Practice providing effective and efficient feedback.

Research

We conducted multiple assessments of these online modules to measure participants’ learning gains and skill development. In a pilot study with 300 Computer Science TAs, we randomly assigned half to complete the modules prior to the beginning of the semester while the other half were used as controls. All students were given pre and post assessments of their knowledge and skills related to grading and providing feedback regardless of whether or not they completed the modules. The treatment group who completed the modules showed significant increases across a wide variety of skills. We then replicated this finding with graduate students across multiple quantitative disciplines.

We then wanted to know how our online modules compare to our equivalent in-person TA training seminar, focusing on the authentic task of providing written feedback on student work. We compared scores from the in-person seminar participants to those of students who completed the same assessment task associated with the online modules. We found that learning gains were consistent across both online and in person formats.

 

Hershock, C., Melville, M. C., Stimson, J., & Dwyer, H. (2022). How effective is asynchronous, online training for graduate and undergraduate student instructors? Journal of Applied Research in Higher Education, (ahead-of-print).

 

Other course details

The entire course can be completed in about 90-120 minutes.

Summer 2023

The Eberly Center for Teaching Excellence and Educational Innovation at Carnegie Mellon University

System requirements

OLI system requirements, regardless of course:

  • internet access
  • an operating system that supports the latest browser update
  • the latest browser update (Chrome recommended; Firefox, Safari supported; Edge and Internet Explorer are supported but not recommended)
  • pop-ups enabled
  • cookies enabled

Some courses include exercises with exceptions to these requirements, such as technology that cannot be used on mobile devices.

This course’s system requirements:

  • none listed (subject to change)

Included instructor tools

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